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behrica/gist:3b2e2716f5f086a76b6ce173e4152660

Created October 3, 2021 00:23
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gistfile1.txt
{:fit-ctx {:metamorph/mode :fit, :metamorph/data Group: 3 [120 5]:
| :sepal_length | :sepal_width | :petal_length | :petal_width | :species |
|--------------:|-------------:|--------------:|-------------:|---------:|
| 4.5 | 2.3 | 1.3 | 0.3 | 1.0 |
| 5.8 | 2.7 | 3.9 | 1.2 | 0.0 |
| 6.3 | 2.7 | 4.9 | 1.8 | 2.0 |
| 7.1 | 3.0 | 5.9 | 2.1 | 2.0 |
| 6.3 | 3.4 | 5.6 | 2.4 | 2.0 |
| 6.4 | 3.2 | 4.5 | 1.5 | 0.0 |
| 6.8 | 3.0 | 5.5 | 2.1 | 2.0 |
| 6.0 | 2.2 | 5.0 | 1.5 | 2.0 |
| 5.5 | 2.5 | 4.0 | 1.3 | 0.0 |
| 6.0 | 3.0 | 4.8 | 1.8 | 2.0 |
| 5.5 | 2.4 | 3.8 | 1.1 | 0.0 |
| 4.8 | 3.4 | 1.6 | 0.2 | 1.0 |
| 5.1 | 3.8 | 1.5 | 0.3 | 1.0 |
| 6.4 | 3.2 | 5.3 | 2.3 | 2.0 |
| 6.9 | 3.1 | 4.9 | 1.5 | 0.0 |
| 6.2 | 2.9 | 4.3 | 1.3 | 0.0 |
| 7.4 | 2.8 | 6.1 | 1.9 | 2.0 |
| 5.5 | 2.6 | 4.4 | 1.2 | 0.0 |
| 4.9 | 2.4 | 3.3 | 1.0 | 0.0 |
| 6.5 | 3.0 | 5.2 | 2.0 | 2.0 |
| 5.7 | 2.8 | 4.1 | 1.3 | 0.0 |
| 6.3 | 2.9 | 5.6 | 1.8 | 2.0 |
| 5.6 | 3.0 | 4.1 | 1.3 | 0.0 |
| 5.7 | 2.6 | 3.5 | 1.0 | 0.0 |
| 5.5 | 3.5 | 1.3 | 0.2 | 1.0 |
,
#uuid "e2663a08-24d8-42b2-9c01-13f673c90456"
{:options {:model-type :smile.classification/random-forest},
:id #uuid "7c7be793-0124-4b4c-b6cc-9d9310f31942",
:feature-columns
[:sepal_length :sepal_width :petal_length :petal_width],
:target-columns [:species],
:target-categorical-maps
{:species
{:lookup-table
{"versicolor" 0, "setosa" 1, "virginica" 2},
:src-column :species,
:result-datatype :float64}}}},
:timing-fit 17,
:train-transform
{:timing 11,
:ctx {:metamorph/mode :transform, :metamorph/data :_unnamed [120 4]:
| versicolor | setosa | virginica | :species |
|-----------:|-----------:|-----------:|---------:|
| 0.03262933 | 0.94031888 | 0.02705179 | 1.0 |
| 0.89342993 | 0.03440937 | 0.07216071 | 0.0 |
| 0.16233375 | 0.03224148 | 0.80542476 | 2.0 |
| 0.05217262 | 0.02765075 | 0.92017663 | 2.0 |
| 0.06330326 | 0.03108576 | 0.90561098 | 2.0 |
| 0.86755117 | 0.04107509 | 0.09137374 | 0.0 |
| 0.05272290 | 0.02689582 | 0.92038128 | 2.0 |
| 0.54642432 | 0.04647174 | 0.40710394 | 0.0 |
| 0.89254353 | 0.03302937 | 0.07442710 | 0.0 |
| 0.20644025 | 0.03653363 | 0.75702612 | 2.0 |
| 0.89186525 | 0.03328015 | 0.07485460 | 0.0 |
| 0.02395460 | 0.95241532 | 0.02363008 | 1.0 |
| 0.02395460 | 0.95241532 | 0.02363008 | 1.0 |
| 0.05500222 | 0.02799871 | 0.91699907 | 2.0 |
| 0.64220164 | 0.04489904 | 0.31289932 | 0.0 |
| 0.89325000 | 0.03402974 | 0.07272026 | 0.0 |
| 0.05355795 | 0.02851712 | 0.91792492 | 2.0 |
| 0.89167118 | 0.03278450 | 0.07554433 | 0.0 |
| 0.85292411 | 0.05895094 | 0.08812495 | 0.0 |
| 0.05163446 | 0.02713734 | 0.92122820 | 2.0 |
| 0.89273983 | 0.03447736 | 0.07278281 | 0.0 |
| 0.05861332 | 0.02835752 | 0.91302917 | 2.0 |
| 0.89093239 | 0.03634010 | 0.07272751 | 0.0 |
| 0.89055330 | 0.03453622 | 0.07491048 | 0.0 |
| 0.05654295 | 0.91688353 | 0.02657353 | 1.0 |
,
#uuid "e2663a08-24d8-42b2-9c01-13f673c90456"
{:model-data
[-84, -19, 0, 5, 115, 114, 0, 33, 115, 109, 105, 108, 101, 46,
113, 0, 126, 0, 66, 0, 0, 0, 5, 0, 0, 0, 0, 117, 113, 0, 126,
...
...
...
0, 0, 0, 0, 41, 0, 0, 0, 0, 64, 4, -52, -52, -52, -52, -52,
-52, 113, 0, 126, 0, 76, 0, 0, 0, 3, 112, 113, 0, 126, 0,
89],
:options {:model-type :smile.classification/random-forest},
:id #uuid "7c7be793-0124-4b4c-b6cc-9d9310f31942",
:feature-columns
[:sepal_length :sepal_width :petal_length :petal_width],
:target-columns [:species],
:target-categorical-maps
{:species
{:lookup-table {"versicolor" 0, "setosa" 1, "virginica" 2},
:src-column :species,
:result-datatype :float64}}},
:scicloj.metamorph.ml/feature-ds Group: 3 [30 4]:
| :sepal_length | :sepal_width | :petal_length | :petal_width |
|--------------:|-------------:|--------------:|-------------:|
| 5.6 | 2.9 | 3.6 | 1.3 |
| 5.2 | 3.4 | 1.4 | 0.2 |
| 6.2 | 2.8 | 4.8 | 1.8 |
| 5.7 | 3.0 | 4.2 | 1.2 |
| 5.7 | 2.8 | 4.5 | 1.3 |
| 5.1 | 3.8 | 1.6 | 0.2 |
| 6.0 | 2.2 | 4.0 | 1.0 |
| 6.1 | 3.0 | 4.9 | 1.8 |
| 6.4 | 2.9 | 4.3 | 1.3 |
| 4.9 | 3.1 | 1.5 | 0.1 |
| 6.2 | 2.2 | 4.5 | 1.5 |
| 5.7 | 4.4 | 1.5 | 0.4 |
| 5.4 | 3.4 | 1.5 | 0.4 |
| 5.5 | 2.3 | 4.0 | 1.3 |
| 6.7 | 3.3 | 5.7 | 2.1 |
| 6.5 | 3.2 | 5.1 | 2.0 |
| 5.0 | 3.2 | 1.2 | 0.2 |
| 4.3 | 3.0 | 1.1 | 0.1 |
| 6.1 | 2.6 | 5.6 | 1.4 |
| 5.7 | 2.9 | 4.2 | 1.3 |
| 5.9 | 3.0 | 4.2 | 1.5 |
| 5.5 | 4.2 | 1.4 | 0.2 |
| 5.8 | 2.7 | 4.1 | 1.0 |
| 5.9 | 3.2 | 4.8 | 1.8 |
| 6.3 | 3.3 | 6.0 | 2.5 |
,
:scicloj.metamorph.ml/target-ds Group: 3 [30 1]:
| :species |
|---------:|
| 0.0 |
| 1.0 |
| 2.0 |
| 0.0 |
| 0.0 |
| 1.0 |
| 0.0 |
| 2.0 |
| 0.0 |
| 1.0 |
| 0.0 |
| 1.0 |
| 1.0 |
| 0.0 |
| 2.0 |
| 2.0 |
| 1.0 |
| 1.0 |
| 2.0 |
| 0.0 |
| 0.0 |
| 1.0 |
| 0.0 |
| 0.0 |
| 2.0 |
},
:metric 0.9333333333333333},
:loss-or-accuracy :accuracy,
:pipe-decl
[[:tech.v3.dataset.metamorph/set-inference-target [:species]]
[:tech.v3.dataset.metamorph/categorical->number [:species]]
[:tech.v3.dataset.metamorph/update-column
:species
:scicloj.metamorph.ml-test/do-xxx]
[:tech.v3.dataset.metamorph/update-column
:species
:clojure.core/identity]
[:scicloj.metamorph.ml/model
{:model-type :smile.classification/random-forest}]],
:source-information
{:fn-sources
{scicloj.metamorph.ml-test/do-xxx
{:code-source nil, :code-local-source "(defn do-xxx [col] col)\n"},
scicloj.metamorph.ml/model
{:code-source
"(defn model\n \"Executes a machine learning model in train/predict (depending on :mode)\n from the `metamorph.ml` model registry.\n\n The model is passed between both invocation via the shared context ctx in a\n key (a step indentifier) which is passed in key `:metamorph/id` and guarantied to be unique for each\n pipeline step.\n\n The function writes and reads into this common context key.\n\n Options:\n - `:model-type` - Keyword for the model to use\n\n Further options get passed to `train` functions and are model specific.\n\n See here for an overview for the models build into scicloj.ml:\n\n https://scicloj.github.io/scicloj.ml/userguide-models.html\n\n Other libraries might contribute other models,\n which are documented as part of the library.\n\n\n metamorph | .\n -------------------------------------|----------------------------------------------------------------------------\n Behaviour in mode :fit | Calls `scicloj.metamorph.ml/train` using data in `:metamorph/data` and `options`and stores trained model in ctx under key in `:metamorph/id`\n Behaviour in mode :transform | Reads trained model from ctx and calls `scicloj.metamorph.ml/predict` with the model in $id and data in `:metamorph/data`\n Reads keys from ctx | In mode `:transform` : Reads trained model to use for prediction from key in `:metamorph/id`.\n Writes keys to ctx | In mode `:fit` : Stores trained model in key $id and writes feature-ds and target-ds before prediction into ctx at `:scicloj.metamorph.ml/feature-ds` /`:scicloj.metamorph.ml/target-ds`\n\n\n\n\n See as well:\n\n * `scicloj.metamorph.ml/train`\n * `scicloj.metamorph.ml/predict`\n\n \"\n\n [options]\n (fn [{:metamorph/keys [id data mode] :as ctx}]\n (case mode\n :fit (assoc ctx id (train data options))\n :transform (do\n (assoc ctx\n ::feature-ds (cf/feature data)\n ::target-ds (cf/target data)\n :metamorph/data (predict data (get ctx id)))))))",
:code-local-source nil},
tech.v3.dataset.metamorph/set-inference-target
{:code-source
"(defn set-inference-target\n \"Set the inference target on the column. This sets the :column-type member\n of the column metadata to :inference-target?.\"\n [dataset target-name-or-target-name-seq]\n (let [colnames (if (sequential? target-name-or-target-name-seq)\n target-name-or-target-name-seq\n [target-name-or-target-name-seq])]\n (ds-base/update-columns dataset colnames\n #(vary-meta % assoc :inference-target? true))))",
:code-local-source nil},
species {:code-source nil, :code-local-source nil},
clojure.core/identity
{:code-source
"(defn identity\n \"Returns its argument.\"\n {:added \"1.0\"\n :static true}\n [x] x)",
:code-local-source nil},
tech.v3.dataset.metamorph/update-column
{:code-source
"(defn update-column\n \"Update a column returning a new dataset. update-fn is a column->column\n transformation. Error if column does not exist.\"\n [dataset col-name update-fn]\n (errors/when-not-error\n dataset\n \"No dataset passed in to update-column.\")\n (ds-proto/update-column dataset col-name update-fn))",
:code-local-source nil},
tech.v3.dataset.metamorph/categorical->number
{:code-source
"(defn categorical->number\n \"Convert columns into a discrete , numeric representation\n See tech.v3.dataset.categorical/fit-categorical-map.\"\n ([dataset filter-fn-or-ds]\n (categorical->number dataset filter-fn-or-ds nil nil))\n ([dataset filter-fn-or-ds table-args]\n (categorical->number dataset filter-fn-or-ds table-args nil))\n ([dataset filter-fn-or-ds table-args result-datatype]\n (update dataset filter-fn-or-ds\n (fn [filtered-ds]\n (reduce\n (fn [filtered-ds colname]\n (let [fit-data\n (ds-cat/fit-categorical-map\n filtered-ds colname table-args result-datatype)]\n (ds-cat/transform-categorical-map filtered-ds fit-data)))\n filtered-ds\n (column-names filtered-ds))))))",
:code-local-source nil},
model-type {:code-source nil, :code-local-source nil},
smile.classification/random-forest
{:code-source nil, :code-local-source nil}},
:classpath
("test"
"src"
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"/home/carsten/.m2/repository/org/bytedeco/mkl/2020.3-1.5.4/mkl-2020.3-1.5.4-windows-x86_64-redist.jar")}}
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